Conventional statistical process control (SPC) charting, an efficient monitoring and diagnosis scheme, is under development in several fields of healthcare monitoring. Investigation of clinical binary outcomes using risk-adjusted (RA) control charts is an important subject in this area. Different researchers have extended the monitoring of the binary outcomes of cardiac surgeries by fitting a logistic model for a patient’s death probability against the patient’s risk. As a result, different RA-based cumulative sum (CUSUM) charts have been proposed for monitoring a patient’s 30-day mortality in several studies. Here, a novel run rules method is introduced in conjunction with the RA CUSUM control chart. The suggested approach was tested and benchmarked through simulation studies based on the average run length (ARL) metric. The outcomes showed favourable results, and further analysis under beta-distributed conditions confirmed its robustness. A worked example was presented to illustrate its implementation.

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